Literature Review
Reviewed over 15 papers and articles on yogic learning, movement science, and mixed reality.
Motor Learning
This section covers my literature review on movement and motor learning. There's growing interest in understanding movement quality in fields like physical health. I'll explain what "movement quality" means in yoga and why it's important for yogic education.
Significance
My research began with a deep dive into motor learning literature. I found a rising need to explore movement qualities, especially in physical health. Labanotation, developed by Rudolf Von Laban in 1928, uses an Effort Graph to visualize the eight elements of movement quality. While these symbols help clarify and communicate movement, their complexity makes them difficult for the average person to use and understand.
Signs for body parts in Labanotation
Laban's Effort Graph
Quality Movement in Yoga
In yoga, having good movement quality means your joints can move freely and adjust easily. Functional movement is about moving in ways that help with everyday tasks. Some might think "pretzel-like" yoga poses or deep stretches aren't practical. However, yoga actually makes everyday movements better. Functional movements are complex, using many muscles and joints together. Over time, some yogis created special ways to combine movements, leading to different yoga styles like "Hatha Yoga."
Understand Movement Quality's Role in Yogic Learning
Sample Study Group
My literature review led me to focus on movement qualities in physical education. To understand how movement quality impacts the learning process, I observed and interviewed a group of yoga practitioners.
(Territory Map Part I) The diagram above illustrates my scoping process.
Research Methods & Questions
I used observation studies to reveal unconscious attitudes and in-depth interviews to understand Yogis' opinions and desires regarding movement quality. My research questions were guided by these four themes:
- Learning Expectations
- Awareness of Movement Quality
- Means of Understanding Movement Quality
- Body Execution of Movement Quality
(Territory Map Part II) The diagram above illustrates understand movement quality’s role in Yogic learning.
Observation Studies & Interviews
I conducted observation studies of two yoga classes with over 20 learners and seven in-depth interviews. Below is photo of the observed yoga class and some sample interview questions:
- Why you decided to join this yoga class? What is your learning goal?
- What are the different components in Hatha yoga you think you need to learn?
- Have you tried other ways of learning yoga other than yoga class? What do you like/dislike about it?
- Do you see any differences between how your body moves versus how the instructor’s body moves? Can you describe them?
Observation Study of Yoga Class during quarantine for covid 2022.
Identifying User & Needs
The diagram below outlines my target users, beginner-to-intermediate yogis familiar with yoga sequences. It also details their subgoals, all contributing to one main objective.
Enhancing body movement technique through discovering new movement qualities and body knowledge to achieve proper form alignment.
Target Users Diagram
Test Existing Theories & Methods
Step 1: Search Relevant Theories & Methods
With this design goal in mind, my next step was to search for existing theories and methods of movement quality exploration and test them with users to find out what works and what does not, what are the expectations and concerns.
Somaesthetics:
- This methodology emphasizes the importance of bodily awareness. This theory’s main contributor, Richard Shusterman, argues that a heightening of somatic consciousness would not only increase the perceptual awareness of meanings and feelings, but also enhance artistic appreciation and creation (Shusterman, R., 2012). This theory offers two ways of viewing the body: viewing the body as an external machine that works independently from the mind, the other one is viewing the body as an internal vehicle that functions as the extension of the mind.
Making Strange:
- This methodology (Loke, L. & Robertson,T., 2013) offers various analytical and experiential ways to de-familiarize the movements of the body. For example, “Finding Pathways” is identifying the specific part of the body that yogis use when they move, and changing the moving sequences of those parts. And “Imagery” is using descriptive metaphors to discover new movement qualities, such as “perform Dancers Pose like you are a growing tree.” This methodology argues that these methods enable: an investigation into the experience of movement, and can open up new spaces in the design of artifacts and technologies.
Theory of Somaesthetics
“Making Strange“ Methodology
Test Existing Theories & Methods
Step 2: Design the Workshop
Based on this research, I came up with the activity framework for an exploratory user workshop, which is illustrated below. I grouped variables that could effect movement quality based on the found concepts and methods, and created prompts that ask participants to sequentially experience the changes of these variables while performing asanas, and experience the resulting movement qualities with and without seeing themselves.
The major goal of the workshop was to test the effectiveness of these prompts as a way to heighten yogis somatic consciousness and thus discover new movement qualities. Participants were asked to follow a series of analytical and experiential prompts that identify some of the variables summarized in the framework, then move their body accordingly. For example, an analytical prompt would ask participants to change the kinematic parameter of a specific body part, and an experiential prompt would ask participants to perform a yoga asana with an imagery in mind (perform Dancers Pose as if your are a growing tree).
Workshop Activity Framework
Test Existing Theories & Methods
Step 3: Conduct the Workshop
I recruited five yogis to participate in this exploratory user workshop. During discussion, participants are positive about the helpfulness of using different types of prompts to increase yogis body awareness and discover new movement qualities during form alignment. Compared to the conventional way of discovering new movement quality through other yogis, this approach embarks on a journey of self-discovery, which offers greater possibilities in understanding the relations between movement quality and the body, the mind and thus expanding the range of body expressiveness when mastering asanas.
Analytical Prompt
Experiential Prompt
Competitive Analysis
My competitive analysis shows the unique position of this design. Existing yoga and motor learning products fall short in providing deep movement quality insights. This XR tool addresses that gap more effectively than my competitors.
Part I: Comparison with Current Yoga Practice Venues
This table highlights how my proposed tool surpasses traditional and digital yoga practices in key areas of movement quality feedback and practice.
Comparison Chart
Competitive Analysis
Part II: Comparison with Relevant Innovative Works
My literature review showed that learning methods are shifting from traditional approaches to computer vision, making mixed reality (MR) a promising technology for learning. Body tracking technologies (like Microsoft Kinect for motion or Athos Suit for muscle activity) can greatly enhance yogic learning when combined with MR. My analysis of MR tools revealed that many focus on learning postures or artistic uses, but few address finding and understanding movement qualities.
The three works shown below are attempts that use MR to explore movement qualities:
MoComp
A tool that visually compares motion capture data (Malmstrom, C. etal, 2016). While useful for spotting movement differences, it doesn't work in real time. Yogis must use separate tools to capture motion and pause their asanas to review the data.
Real-time 3D Simulation
This system displays movement qualities in real-time 3D shapes and motion trails (Tsampounaris, G. et al, 2016). While it encourages self-reflection, it lacks motivation or goals (like prompts), which can leave yogis confused by disconnected visuals. Also, it can't compare current and past movements, hindering effective practice reflection.
36: Physio@Home
This concept proposed an augmented mirror for visual guidance during physiotherapy exercises (Tang, R. et al, 2015). Because it's designed for physical therapy, it only shows one 'correct' way to move, rather than offering a variety of movement qualities.
Speed Dating of System Concepts
Next, I designed a system to help yogis learn different yoga moves on their own. I created three main ideas and drew them out as storyboards. Then, I showed these storyboards to yogis and asked for their feedback.
System Concepts
AR Glasses
Yogis worried about how useful and expensive these new systems would be. AR glasses could offer touch or 3D feedback. However, they might be very costly and could also get in the way of yogis' movements.
Digital Application
An app with mixed reality features seemed like a good option. Yogis want real-time feedback on an easy-to-use platform. We also thought about a gaming console that tracks movement, as its feedback feels very natural.
Designing the System and User Experience
After exploring different ideas, I decided to create a special feature for motion-controlled games, like those on the Nintendo Switch. This feature helps people improve their movement skills in a private, safe space. Here's how it works: First, a user (let's call them a "yogi") buys the product online. They get digital content and then install the app or software. This app can connect to a larger screen so they can see their whole body. A webcam tracks their movements and gives live feedback. The yogi can use their Joy-Cons to control the app and practice moving correctly.
System Map
User Journey Map
The app includes a "Create Mode" where yogis can freely explore movement. In this mode, they can better understand their own body. They can follow guides from different categories to learn new yoga poses and master their body alignment. As they explore, yogis can use visual guides to compare their live movements with a recorded video of themselves or a virtual coach. To bring this to life, I first mapped out how users would interact with the system, then sketched the app screens, and finally made detailed wireframes.
Development of Functional Prototype
To confirm the viability of the proposed tool using current or near-future technologies, I produced a functional prototype to realize the motion tracking and visual overlay display features integrated in the exploration process. Making a digital tool that connects physical movement with visual feedback by collaborating with an engineer to combine the biomechanics of movement with sensor data, video capture technology, and cloud-based software.
Computational Innovation Design: Bridging Physical Motion and Digital Feedback
The tool works like this: a line shows where a movement starts and how it changes over time. A sphere shows how long you hold a certain movement. Fast movements create smaller spheres, while slow movements create larger ones.
Functional Prototype in Unity
I built a functional prototype in Unity using movement data from a Kinect sensor.
Development of Functional Prototype
Since one of the design principles I found was the importance of comparative feedback, the first step I took was to determine what types of feedback should be provided to aid movement comparison. I created graphic and interactive prototypes and tested them with yogis to hear their thoughts.
Iterative Testing & Learnings
Through iterative testing with 5 users, I learned that simple, expressive feedback visuals — like color gradients and line motion — were more effective than numerical metrics.
Testing
I tested an early version of the computational design prototype, and watched participants learn how to do the Dancer Pose (Natarajasana). After observing how they learned the correct alignment and technique, I analyzed the results. This helped me find what was difficult, frustrating, and how I could make things better.
Visual Feedback: Balance
Visual Feedback:: Flexibility
Visual Feedback: Strength
Refining Visual Feedback
Based on this, I refined the visual feedback to emphasize flow and form continuity, rather than accuracy, encouraging users to focus on awareness instead of correction (i.e. seen in red).
Outcome and Impact
Living Visual System
The final prototype transformed real-time motion into a living visual system that supported reflection and self-guided improvement.
Design Integration
It demonstrated how data visualization, interaction design, and emotion can work together to create new learning experiences.
Computational Empathy
The project was showcased in my MFA thesis exhibition as an example of computational empathy, using data and feedback to build confidence instead of judgment.
Balance Scenario
Strength Scenario
Flexibility Scenario